Effects of the Earth curvature on Mie-scattering radiances at high solar-sensor geometries based on Monte Carlo simulations.

Given the importance of vector radiative transfer models in ocean color remote sensing and a lack of suitable models capable of analyzing the Earth curvature effects on Mie-scattering radiances, this study presents an enhanced vector radiative transfer model for a spherical shell atmosphere geometry by the Monte Carlo method (MC-SRTM), considering the effects of Earth curvature, different atmospheric conditions, flat sea surface reflectance, polarization, high solar and sensor geometries, altitudes and wavelengths. A Monte Carlo photon transport model was employed to simulate the vector radiative transfer processes and their effects on the top-of-atmosphere (TOA) radiances. The accuracy of the MC-SRTM was verified by comparing its scalar model outputs from Henyey-Greenstein (HG) phase function with the Kattawar-Adams model results, and the mean relative differences were less than 2.75% and 4.33% for asymmetry factors (g-values) of 0.5 and 0.7, respectively. The vector mode results of MC-SRTM for a spherical shell geometry with the Mie-scattering phase matrix were compared with the PCOART-SA model results (from Polarized Coupled Ocean-Atmosphere Radiative Transfer model based on the pseudo-spherical assumption), and the mean relative differences were less than 2.67% when solar zenith angles (SZAs) > 70 ∘ and sensor viewing zenith angles (VZAs) < 60 ∘ for two aerosol models (coastal and tropospheric models). Based on the MC-SRTM, the effects of Earth curvature on TOA radiances at high SZAs and VZAs were analyzed. For pure aerosol atmosphere, the effects of Earth curvature on TOA radiances reached up to 5.36% for SZAs > 70 ∘ and VZAs < 60 ∘ and reduced to less than 2.60% for SZAs < 70 ∘ and VZAs > 60 ∘. The maximum Earth curvature effect of pure aerosol atmosphere was nearly same (10.06%) as that of the ideal molecule atmosphere. The results also showed no statistically significant differences for the aerosol-molecule mixed and pure aerosol atmospheres. Our study demonstrates that there is a need to consider the Earth curvature effects in the atmospheric correction of satellite ocean color data at high solar and sensor geometries.

Enhanced POLYMER atmospheric correction algorithm for water-leaving radiance retrievals from hyperspectral/multispectral remote sensing data in inland and coastal waters.

Accurate retrieval of the water-leaving radiance from hyperspectral/multispectral remote sensing data in optically complex inland and coastal waters remains a challenge due to the excessive concentrations of phytoplankton and suspended sediments as well as the inaccurate estimation and extrapolation of aerosol radiance over the visible wavelengths. In recent years, reasonably accurate methods were established to estimate the enhanced contribution of suspended sediments in the near-infrared (NIR) and shortwave infrared (SWIR) bands to enable atmospheric correction in coastal waters, but solutions to derive the dominant phytoplankton contribution in the NIR and SWIR bands are less generalizable and subject to large uncertainties in the remotely-derived water color products. These issues are not only associated with the standard atmospheric correction algorithm in the SeaDAS processing system but with the non-traditional algorithms such as POLYMER (POLYnomial-based approach established for the atmospheric correction of MERIS data). This study attempts to enhance the POLYMER algorithm to enable atmospheric correction of hyperspectral and multispectral remote sensing data over a wide range of inland and ocean waters. The original POLYMER algorithm is less suitable owing to its complete reliance on a polynomial approach to model the atmospheric reflectance as a function of the wavelength and retrieve the water-leaving reflectance using two semi-analytical models (MM01 and PR05). The polynomial functions calculate the bulk atmospheric contribution instead of using an explicit method to estimate aerosol radiance separately, resulting the erroneous water color products in inland and coastal waters. The modified POLYMER algorithm (mPOLYMER) employs more realistic approaches to estimate aerosol contributions with a combination of UV and Visible-NIR bands and enables accurate retrievals of water-leaving radiance from both hyperspectral and multispectral remote sensing data. To assess the relative performance and wider applicability of mPOLYMER, the original and enhanced algorithms were tested on a variety of HICO, MSI and MODIS-Aqua data and the retrieved Lwn products were compared with AERONET-OC and OOIL-regional in-situ data. Expectedly, the mPOLYMER algorithm greatly improved the accuracy of Lwn (in terms of magnitude and spectral shape) when applied to MODIS-Aqua and HICO data in highly turbid productive waters (with higher concentrations of phytoplankton or with dense algal blooms) in Muttukadu Lagoon, Lake Erie, Yangtze River Estuary, Baltic Sea and Arabian Sea. In contrast, the original POLYMER algorithm overestimated Lwn in the visible and NIR bands and produced unphysical negative Lwn or distorted Lwn spectra in turbid productive waters. The mPOLYMER yielded a relative mean error reduction of more than 50% (i.e., from 79% to 34%) in Lwn for a large number of matchup data. The improved accuracy and data quality is because the mPOLYMER algorithm's funio and coefficients sufficiently accounted for the enhanced backscattering contribution of phytoplankton and suspended sediments in optically complex waters.

Fuzzy-based global water quality assessment and water quality cells identification using satellite data.

The water environmental impact assessment and management programs increasingly rely on accurate and quantitative estimates of water quality parameters through remote sensing, owing to the limitation of the time-consuming field-based approaches. Numerous studies have utilised the remote-derived water-quality products and existing water quality index WQI models, but they are typically site-specific and yield significant errors for the accurate assessment and monitoring of coastal and inland water bodies. This study presents a generalized WQI model that incorporates a flexible number of parameters, simplifying them to produce comprehensive water quality index values with the fuzzy logic approach. To derive these index values, three major water quality parameters such as Chl, TSS and aCDOM443 were estimated using new remote-sensing models, and the corresponding indices Trophic State Index (TSI), Total Suspended Solids Index (TSSI) and CDOM Index (CI) were produced by a generalized index model. Finally, WQI products were derived based on the Mamdani-based Fuzzy Inference System (FIS) and individual contribution of the water quality parameters to WQI was analysed to establish 'Water Quality Cells' WQcells, which are represented by the dominant WQ parameter. The new models were tested on MODIS-Aqua and Sentinel-3 OLCI data in different regional and global oceanic waters. Further, a time series analysis was performed in regional coastal oceanic waters (along the Indian coast) to study the seasonal variations of individual water quality parameters and WQI over the period from 2011 to 2020. The results demonstrated that the FIS is efficient in handling the parameters with varying units and their relative importance. The water quality cells were identified in the bloom-dominated (Arabian Sea), TSS-dominated (Point Calimere, India and Yangtze River estuary, China) and CDOM-dominated (South Carolina coast, USA) regions. The time series analysis revealed that the water quality of the Indian coast exhibits cyclic seasonal variations due to the annual occurrence of the south-west and north-east monsoons. These results are critical for monitoring and assessing the quality of surface waters in coastal and inland environments and enabling water resources managers to formulate and implement management plans for a variety of water bodies cost-effectively.

New algorithm for computation of the Rayleigh-scattering radiance for remote sensing of water color from space.

Rayleigh-scattering radiance (Lr) calculations based on the standard algorithm are often associated with significant uncertainties leading to inconsistent water-leaving radiance retrievals, both spatially and temporally across latitudes and altitudes. The uncertainty could result from the use of Rayleigh lookup tables generated for the standard surface atmospheric pressure and hence the Rayleigh optical thickness (ROT) at the specific atmospheric pressure regardless of its daily and seasonal variations. This study presents a new algorithm (hereafter referred to as the refined algorithm) to compute the Rayleigh-scattering radiance that relies on accurate calculations of the ROT as a function of the composition of air (CO2 volume concentration), surface atmospheric pressure and relative air mass for given sun-sensor geometries. As CO2 is well mixed throughout the atmospheric column, the CO2 volume concentrations derived from this study agree well with measurements in different seasons across studied latitudes. Relative air mass has a significant effect on the ROT and that is calculated as a function of apparent sun-sensor zenith angles with the variations in pressure and thermal characteristics of the atmosphere. Thus, the results indicate significant variations of ROT and air mass with location on the earth's surface and their influence on the Lr, particularly in the UV-Blue region of the spectrum. The refined algorithm for calculating the Lr is tested on several MODIS-Aqua Level 1A data and the relative errors in Rayleigh-scattering radiance and normalized water-leaving radiance (Lwn) retrievals between the refined algorithm and standard (SeaDAS) algorithm are compared using in-situ measurement data collected at MOBY (clear ocean), AERONET (turbid coastal ocean), and NOMAD (clear ocean) sites. The results indicate that the Lr calculated using the SeaDAS algorithm are mostly underestimated and show significant departures with the Lr calculated using the refined algorithm. This departure induced by the SeaDAS algorithm to Lr becomes larger with decreasing wavelength (ΔLr from -2.38% at 412 nm to 1.69% at 678 nm), which causes errors in Lwn retrievals (ΔLwn) of up to 26.48% at 412 nm and 13.34% at 678 nm. The overall improvements in the retrieved Lwn values achieved vary from 56% at 412 nm to 29% at 678nm, which yield similar improvements in Lwn retrievals with lower errors and higher slopes and correlation coefficients when compared with the in-situ Lwn data. These results indicate that the refined algorithm for computation of the Lr can yield more accurate Lwn retrievals and produce spatially and temporally consistent biogeochemical products at different latitudes and altitudes as desired by the scientific community.

UV-NIR approach with non-zero water-leaving radiance approximation for atmospheric correction of satellite imagery in inland and coastal zones.

In the atmospheric correction process of the satellite ocean color data, the removal of the aerosol scattering contribution over the coastal and inland water bodies has been a major challenge with the standard algorithms. In this work, a practical method is proposed based on a combination of NIR and ultraviolet (UV) bands (named as UVNIR-ex) for the succeeding generation of space borne multispectral and hyperspectral sensors. This scheme replaces the black-ocean assumption and accounts for non-zero water-leaving radiance contributions in the NIR and UV bands. The aerosol contributions are thus deduced for these two bands and used to select the appropriate aerosol models to retrieve aerosol optical properties and hence, water-leaving radiances in the UV, Visible and NIR bands. The performance of the UVNIR-ex algorithm was tested and evaluated based on match-ups between HICO and in-situ observations in optically complex coastal and inland waters and by comparison with three alternative aerosol correction methods based on UV-NIR, Spectral Shape Parameter (SSP) and iterative NIR (INIR) approaches. A preliminary comparison with in-situ aerosol optical thickness (AOT) measurements from AERONET-OC sites revealed that the UVNIR-ex algorithm significantly improved the AOT retrievals with a mean relative error (MRE) around 25%, while the UVNIR, SSP and INIR algorithms showed performance degradation with a MRE of 27%, 34%, and 42%, respectively. The comparison with AERONET-OC and regional in-situ measurements from turbid and productive waters further showed that the INIR algorithm underestimated the nLw retrievals in blue bands in turbid waters (MRE > 100%) and negligible nLw in red-NIR bands and high anomalous radiances in UV-Blue bands in productive waters (MRE 53%). The SSP and UVNIR algorithms performed better in retrieving the nLw in green-NIR bands but showed significant errors in UV-blue bands in both turbid and productive waters. Based on these match-up analyses, the UVNIR-ex algorithm yielded best nLw retrievals across all the UV-NIR bands in terms of accuracy and performance. The highest accuracy and consistency of the UVNIR-ex algorithm indicates that it is more suited for estimating the aerosol optical properties and water-leaving radiance and has a significant advantage over the requirement of shortwave infrared bands for turbid and productive waters.

Semi-analytical algorithms of ocean color remote sensing under high solar zenith angles.

With the increasing interest in ocean color remote sensing in polar oceans and geostationary ocean color satellite with diurnal observations, it is unavoidable to encounter ocean color retrievals under high solar zenith angles. Under these scenarios, the capability of current remote sensing algorithms is poorly known. In this study, the performance of the two widely used semi-analytical algorithms for the water inherent optical properties (QAA and GSM01) under high solar zenith angle conditions were firstly evaluated based on global in situ data set (SeaBASS-NOMAD). The results showed that the performances of both QAA and GSM01 degraded significantly with the increasing in solar zenith angle (SZA), and the biases increased about 1.3-fold when SZA varied from 30° to 80°. The high uncertainties at high SZA was mainly induced by the systematic overestimation of the key parameter u (ratio of backscattering coefficient to the sum of absorption and backscattering coefficients) at high solar zenith angles. Based on the Hydrolight-simulated data set, a new model (NN-algorithm) for retrieving u from remote sensing reflectance was developed for high solar zenith angle conditions using the neural network method. The validation results revealed that the NN-algorithm could improve the estimation of parameter u and further ocean color products. In addition, our results indicate that a more accurate atmosphere correction is needed to deal with ocean color remote sensing data acquired under large solar zenith angle conditions.

New theoretical formulation for the determination of radiance transmittance at the water-air interface: reply.

Gordon and Voss in their comment challenge the recently published paper [Opt. Express25, 27086 (2017)] on the unity factor of radiance transmittance of the assumed hypothetical case (i.e., for the albedo equal to 1) and question the dependence of particulate contribution to the refractive index of water. Here, we provide answers to their comments.

Monte Carlo simulations of the backscattering measurements for associated uncertainty.

Three-dimensional simulations using the Monte Carlo method are implemented to analyze and quantify the uncertainty and the influence of absorption on the measurement of light backscattering by ECO-BB9 (WET Labs) sensor for a wide variety of optically complex and open ocean waters. The analytical investigation of the geometrical configuration revealed a distinct effective path length which contributes towards an accurate assessment of absorption effect on the backscattering measurement. The present study proposes the application of a non-linear relationship to determine the measured parameter from the detector counts more accurately than the conventional method that applies the scale factor. It was found that the mean centroid angle of the instrument shows marginal variations for varying absorption and backscattering coefficients. Nevertheless, the mean centroid angle for the instrument over the entire course of the simulation study was found to be 124° which conforms well with the study of Doxaran et al. [Opt. Express 24, 3615 (2016)].

New theoretical formulation for the determination of radiance transmittance at the water-air interface.

Radiative transfer across the water-air interface has important implications for optics and remote sensing of natural waters. The upward radiance emerging from the water suffers a critical change when it passes through the water-air interface. Upwelling radiance transmittance τw,a is an optical process occurring at the water-air interface that determines the in-water radiances propagating through the interface. In previous studies, τw,a was successfully derived for determining the water-leaving radiances in open ocean waters, despite being oversimplified with a constant value. The constant τw,a value becomes rapidly invalid in high scattering and absorbing waters within nearshore and inland environments. In this study, we attempt to quantitatively solve the upwelling radiance transmittance τw,a (i.e., the percentage of in-water photons that escape through the water-air interface) for varying coefficients of scattering and absorption within the range of natural waters. The two important optical phenomena which are ignored in the previous studies have been fully accounted: (i) the particulate contribution to the refractive index (RI) of seawater and (ii) the multiple interactions of the upwelling photons with the water-air interface. As a result, this study leads to a new theoretical formulation of the upwelling radiance transmittance applicable to all natural waters. The effect and variation of the new formulation on the water-leaving radiance and remote sensing reflectance is further studied for coastal and inland waters. Particular attention is also focused on the conversion of sub-surface remote sensing reflectance (rrs) to above-surface remote sensing reflectance (Rrs), which is important for calibration and validation of the remote sensing algorithms. The results show substantial improvement in the ocean color quantities (Lw and Rrs) by up to factor 33% for scattering waters and <5% for absorbing waters.

Ocean color retrieval from MWI onboard the Tiangong-2 Space Lab: preliminary results.

The Moderate-resolution Wide-wavelengths Imager (MWI) is the ocean color sensor onboard the Chinese Tiangong-2 Space Lab, which was launched on Sept. 15, 2016. The MWI is also an experimental satellite sensor for the Chinese next generation ocean color satellites, HY-1E and HY-1F, which are scheduled for launch around 2021. With 100m spatial resolution and 18 bands in the visible light and infrared wavelengths, MWI provides high quality ocean color observations especially over coastal and inland waters. For the first time, this study presents some important results on water color products generated from the MWI for the oceanic and inland waters. Preliminary validation in turbid coastal and inland waters showed good agreement between the MWI-retrieved normalized water-leaving radiances (Lwn) and in situ data. Further, the MWI-retrieved Lwn values compared well with the GOCI-retrieved Lwn values, with the correlation coefficient greater than 0.90 and mean relative differences smaller than 26.63% (413 nm), 4.72% (443 nm), 3.69% (490 nm), 7.15% (565 nm), 9.45% (665 nm), 8.11% (682.5 nm), 14.68% (750 nm) and 18.55% (865 nm). As for the Level 2 product (e.g, total suspended matter TSM) in turbid Yangtze River Estuary and Hangzhou Bay waters, the relative difference between MWI and GOCI-derived TSM values was ~18.59% with the correlation coefficient of 0.956. In open-oceanic waters, the retrieved MWI-Chla distributions were well consistent with the MODIS/Aqua and VIIRS Chla values products and resolved finer spatial structures of phytoplankton blooms. This study provides encouraging results for the MWI's performance and operational applications in oceanic and inland regions.

Estimation of underwater visibility in coastal and inland waters using remote sensing data.

An optical method is developed to estimate water transparency (or underwater visibility) in terms of Secchi depth (Z sd ), which follows the remote sensing and contrast transmittance theory. The major factors governing the variation in Z sd , namely, turbidity and length attenuation coefficient (1/(c + K d ), c = beam attenuation coefficient; K d  = diffuse attenuation coefficient at 531 nm), are obtained based on band rationing techniques. It was found that the band ratio of remote sensing reflectance (expressed as (R rs (443) + R rs (490))/(R rs (555) + R rs (670)) contains essential information about the water column optical properties and thereby positively correlates to turbidity. The beam attenuation coefficient (c) at 531 nm is obtained by a linear relationship with turbidity. To derive the vertical diffuse attenuation coefficient (K d ) at 531 nm, K d (490) is estimated as a function of reflectance ratio (R rs (670)/R rs (490)), which provides the bio-optical link between chlorophyll concentration and K d (531). The present algorithm was applied to MODIS-Aqua images, and the results were evaluated by matchup comparisons between the remotely estimated Z sd and in situ Z sd in coastal waters off Point Calimere and its adjoining regions on the southeast coast of India. The results showed the pattern of increasing Z sd from shallow turbid waters to deep clear waters. The statistical evaluation of the results showed that the percent mean relative error between the MODIS-Aqua-derived Z sd and in situ Z sd values was within ±25%. A close agreement achieved in spatial contours of MODIS-Aqua-derived Z sd and in situ Z sd for the month of January 2014 and August 2013 promises the model capability to yield accurate estimates of Z sd in coastal, estuarine, and inland waters. The spatial contours have been included to provide the best data visualization of the measured, modeled (in situ), and satellite-derived Z sd products. The modeled and satellite-derived Z sd values were compared with measurement data which yielded RMSE = 0.079, MRE = -0.016, and R 2  = 0.95 for the modeled Z sd and RMSE = 0.075, MRE = 0.020, and R 2  = 0.95 for the satellite-derived Z sd products.

An optical method to assess water clarity in coastal waters.

Accurate estimation of water clarity in coastal regions is highly desired by various activities such as search and recovery operations, dredging and water quality monitoring. This study intends to develop a practical method for estimating water clarity based on a larger in situ dataset, which includes Secchi depth (Z sd ), turbidity, chlorophyll and optical properties from several field campaigns in turbid coastal waters. The Secchi depth parameter is found to closely vary with the concentration of suspended sediments, vertical diffuse attenuation coefficient K d (m(-1)) and beam attenuation coefficient c (m(-1)). The optical relationships obtained for the selected wavelengths (i.e. 520, 530 and 540 nm) exhibit an inverse relationship between Secchi depth and the length attenuation coefficient (1/(c + K d )). The variation in Secchi depth is expressed in terms of undetermined coupling coefficient which is composed of light penetration factor (expressed by z(1%)K d (λ)) and a correction factor (ξ) (essentially governed by turbidity of the water column). This method of estimating water clarity was validated using independent in situ data from turbid coastal waters, and its results were compared with those obtained from the existing methods. The statistical analysis of the measured and the estimated Z sd showed that the present method yields lower error when compared to the existing methods. The spatial structures of the measured and predicted Z sd are also highly consistent with in situ data, which indicates the potential of the present method for estimating the water clarity in turbid coastal and associated lagoon waters.

Semi-analytical modeling and parameterization of particulates-in-water phase function for forward angles.

A model based on Mie theory is described for predicting scattering phase functions at forward angles (0.1°-90°) with particle size distribution (PSD) slope and bulk refractive index as input parameters. The PSD slope 'ξ ' is calculated from the hyperbolic slope of the particle attenuation spectrum measured in different waters. The bulk refractive index 'n' is evaluated by an inversion model, using measured backscattering ratio (Bp) and PSD slope values. For predicting the desired phase function in a certain water type, in situ measurements of the coefficients of particulate backscattering, scattering and beam attenuation are needed. These parameters are easily measurable using commercially available instruments which provide data with high sampling rates. Thus numerical calculation of the volume scattering function is carried out extensively by varying the optical characteristics of particulates in water. The entire range of forward scattering angles (0.1°-90°) is divided into two subsets, i.e., 0.1° to 5° and 5° to 90°. The particulates-in-water phase function is then modeled for both the ranges. Results of the present model are evaluated based on the well-established Petzold average particle phase function and by comparison with those predicted by other phase function models. For validation, the backscattering ratio is modeled as a function of the bulk refractive index and PSD slope, which is subsequently inverted to give a methodology to estimate the bulk refractive index from easily measurable optical parameters. The new phase function model which is based on the exact numerical solution obtained through Mie theory is mathematically less complex and predicts forward scattering phase functions within the desired accuracy.

New model for subsurface irradiance reflectance in clear and turbid waters.

Modeling of subsurface irradiance reflectance fields especially in turbid coastal, harbor and lagoon waters has important applications in ecology, engineering and optical remote sensing. The present study aims at exploring many possible causes of variation in the proportionality factor f and analyzing its effect on the subsurface irradiance reflectance in different waters. A new model is then developed to estimate this optical property as a function of the absorption coefficient (a), backscattering coefficient (bb), incident illumination condition, and other wavelength-depth dependent factors. Implementation of this new model is examined for five types of waters with varying turbidity and chlorophyll. Model results are verified with in situ measurements data and compared with the results from existing models. Formulas already proposed for estimating R in the previous studies and generally expressed by R = 0.33(bb/(a + bb)) or R = f (bb/(a + bb)) where f = 0.975-0.629 µ(0) (µ(0) is the incident photons just below the sea surface) work fairly well in clear oceanic waters, but yield large errors in turbid coastal and lagoon waters due to the use of a constant value ~0.33 or the dimensionless parameter f which does not account for certain processes in the model (e.g., multiple scattering, depth-dependent changes in the diffuse components of solar radiation, and spectral variation in f). By contrast, the new model estimates the reflectances having good agreement with in situ data from just below the water surface and throughout the water column. The improved performance of the present model is because it includes a parameterization of the proportionality factor f which varies with wavelength and depends on the sun angle, inherent optical properties, and diffuse attenuation coefficients. Knowledge related to interrelationships between inherent optical properties and apparent optical properties can be used to study the variability of the subsurface reflectance in homogeneous and stratified coastal waters with respect to many possible causes of its variations.

Monitoring of ocean surface algal blooms in coastal and oceanic waters around India.

The National Aeronautics and Space Administration's (NASA) sensor MODIS-Aqua provides an important tool for reliable observations of the changing ocean surface algal bloom paradigms in coastal and oceanic waters around India. A time series of the MODIS-Aqua-derived OSABI (ocean surface algal bloom index) and its seasonal composite images report new information and comprehensive pictures of these blooms and their evolution stages in a wide variety of events occurred at different times of the years from 2003 to 2011, providing the first large area survey of such phenomena around India. For most of the years, the results show a strong seasonal pattern of surface algal blooms elucidated by certain physical and meteorological conditions. The extent of these blooms reaches a maximum in winter (November-February) and a minimum in summer (June-September), especially in the northern Arabian Sea. Their spatial distribution and retention period are also significantly increased in the recent years. The increased spatial distribution and intensity of these blooms in the northern Arabian Sea in winter are likely caused by enhanced cooling, increased convective mixing, favorable winds, and atmospheric deposition of the mineral aerosols (from surrounding deserts) of the post-southwest monsoon period. The southward Oman coastal current and southwestward winds become apparently responsible for their extension up to the central Arabian Sea. Strong upwelling along this coast further triggers their initiation and growth. Though there is a warming condition associated with increased sea surface height anomalies along the coasts of India and Sri Lanka in winter, surface algal bloom patches are still persistent along these coasts due to northeast monsoonal winds, enhanced precipitation, and subsequent nutrient enrichment in these areas. The occurrence of the surface algal blooms in the northern Bay of Bengal coincides with a region of the well-known Ganges-Brahmaputra Estuarine Frontal (GBEF) system, which increases supply of nutrients in addition to the land-derived inputs triggering surface algal blooms in this region. Low density (initiation stage) of such blooms observed in clear oceanic waters southeast and northeast of Sri Lanka may be caused by the vertical mixing processes (strong monsoonal winds) and the occurrence of Indian Ocean Dipole events. Findings based on the analyses of time series satellite data indicate that the new information on surface algal blooms will have important bearing on regional fisheries, ecosystem and environmental studies, and implications of climate change scenarios.

A new model for the vertical spectral diffuse attenuation coefficient of downwelling irradiance in turbid coastal waters: validation with in situ measurements.

The vertical spectral diffuse attenuation coefficient of Kd is an important optical property related to the penetration and availability of light underwater, which is of fundamental interest in studies of ocean physics and biology. Models developed in the recent decades were mainly based on theoretical analyses and numerical (radiative transfer) simulations to estimate this property in optically deep waters, thus leaving inadequate knowledge of its variability at multiple depths and wavelengths, covering a wide range of solar incident geometry, in turbid coastal waters. In the present study, a new model is developed to quantify the vertical, spatial and temporal variability of K(d) at multiple wavelengths and to quantify its dependence with respect to solar incident geometry under differing sky conditions. Thus, the new model is derived as a function of inherent optical properties (IOPs - absorption a and backscattering b(b)), solar zenith angle and depth parameters. The model results are rigorously evaluated using time-series and discrete in situ data from clear and turbid coastal waters. The K(d) values derived from the new model are found to agree with measured data within the mean relative error 0.02~6.24% and R² 0.94~0.99. By contrast, the existing models have large errors when applied to the same data sets. Statistical results of the new model for the vertical spectral distribution of K(d) in clear oceanic waters (for different solar zenith and in-water conditions) are also good when compared to those of the existing models. These results suggest that the new model can provide an improved interpretation about the variation of the vertical spectral diffuse attenuation coefficient of downwelling irradiance, which will have important implications for ocean physics, biogeochemical cycles and underwater applications in both relatively clear and turbid coastal waters.

Application of satellite infrared data for mapping of thermal plume contamination in coastal ecosystem of Korea.

The 5900 MW Younggwang nuclear power station on the west coast of Korea discharges warm water affecting coastal ecology [KORDI report (2003). Wide area observation of the impact of the operation of Younggwang nuclear power plant 5 and 6, No. BSPI 319-00-1426-3, KORDI, Seoul, Korea]. Here the spatial and temporal characteristics of the thermal plume signature of warm water are reported from a time series (1985-2003) of space-borne, thermal infrared data from Landsat and National Oceanic and Atmospheric Administration (NOAA) satellites. Sea surface temperature (SST) were characterized using advanced very high resolution radiometer data from the NOAA satellites. These data demonstrated the general pattern and extension of the thermal plume signature in the Younggwang coastal areas. In contrast, the analysis of SST from thematic mapper data using the Landsat-5 and 7 satellites provided enhanced information about the plume shape, dimension and direction of dispersion in these waters. The thermal plume signature was detected from 70 to 100 km to the south of the discharge during the summer monsoon and 50 to 70 km to the northwest during the winter monsoon. The mean detected plume temperature was 28 degrees C in summer and 12 degrees C in winter. The DeltaT varied from 2 to 4 degrees C in winter and 2 degrees C in summer. These values are lower than the re-circulating water temperature (6-9 degrees C). In addition the temperature difference between tidal flats and offshore (SSTtidal flats - SSToffsore) was found to vary from 5.4 to 8.5 degrees C during the flood tides and 3.5 degrees C during the ebb tide. The data also suggest that water heated by direct solar radiation on the tidal flats during the flood tides might have been transported offshore during the ebb tide. Based on these results we suggest that there is an urgent need to protect the health of Younggwang coastal marine ecosystem from the severe thermal impact by the large quantity of warm water discharged from the Younggwang nuclear power plant.